This mandate modernizes BI and establishes AI-driven BI as a core enterprise capability—raising the standard for modeling and visualization, operationalizing conversational analytics through LLMs and Databricks Genie, and advancing the organization from descriptive and predictive analytics toward prescriptive insights. The role partners directly with senior leadership and carries enterprise-wide visibility and accountability to accelerate decision velocity, drive adoption, and maximize ROI through a durable insight-to-action operating model.
As the Vice President, Business Intelligence – AI & Advanced Analytics within our enterprise analytics organization, you will modernize BI and establish AI-promoten BI as a core enterprise capability.
Job responsibilities
- Serve as the primary BI partner to senior and executive stakeholders, aligning analytics priorities to strategy, surfacing forward-looking insights, and influencing without authority to drive outcomes.
- Own requirements-to-value delivery across the BI lifecycle, from problem framing and success criteria through UAT, deployment, adoption, and impact measurement, with clear ownership and SLAs.
- Architect and govern the semantic layer: define logical structures, business rules, and metric definitions for Engineering to implement; mentor the team on modeling trade-offs and performance optimization.
- Deliver AI-enabled BI: implement LLM-powered natural language querying (e.g., Databricks Genie), design domain-specific AI assistants, and integrate predictive analytics into decision flows; progressively build prescriptive capabilities as maturity grows.
- Set and enforce visualization standards; personally build and review high-impact Sigma and Tableau assets that emphasize usability, performance, and guided analysis.
- Establish and run an insight-to-action governance model that prioritizes findings, assigns accountable owners, and tracks outcomes to closure; communicate benefits, trade-offs, and risks transparently to senior leaders.
- Define and track portfolio impact metrics — including adoption, decision velocity, decision quality, and ROI — and apply disciplined, risk-adjusted prioritization.
- Lead change management and enablement to drive adoption, including training, quick-reference content, and executive-ready briefings.
- Build team capability through upskilling, code and modeling reviews, visualization critiques, and recruiting hybrid talent with domain and technical depth.
- Maintain a continuous improvement backlog; iterate post–go-live based on feedback and decommission low-value artifacts.
Required qualifications, capabilities and skills
- 10+ years in BI/Analytics experience.
- 3+ years leading teams delivering enterprise-scale BI.
- Demonstrated expertise in logical data modeling.
- Demonstrated expertise in semantic data modeling and semantic layer design.
- Proven metric stewardship (definition, ownership, consistency).
- Hands-on with Sigma and Tableau, including performance optimization.
- Builds governed self-service analytics with row-level security controls.
- Fluent in Advanced SQL and Python for analytics engineering.
- Experience operationalizing LLMs/NLP/conversational AI inside BI workflows.
- Strong prompt engineering capability and familiarity with tools like Databricks Genie.
- Strengths in data governance/metadata management, applied statistics & hypothesis testing, rigorous requirements decomposition/documentation, and executive-ready communication with proven senior stakeholder management and cross-functional influence.
Preferred qualifications, capabilities and skills
- Experience deploying natural-language querying over governed data. Experience building domain-specific AI assistants aligned to business taxonomy.
- Ability to map user intents to standardized terms, metrics, and definitions. Proven track record of driving adoption at scale across teams.
- Demonstrated change management and enablement (training, comms, documentation).
- Evidence that solutions operate within security/entitlements and governance controls.
- Stronger fit with measurable ROI (e.g., time saved, reduced reporting, faster decisions, business impact).
- Ability to turn ambiguity into precise analytical problems and drive urgent insight-to-action, with crisp executive communication and cross-functional influence across Business, Finance, Operations, and Technology.